As man-machine interaction interfaces are developing towards a design of user-friendly operation, computer control interfaces gradually evolve from conventional keyboards, mice, joysticks and touch apparatuses to operation interfaces that capture images of natural gestures or body motions. It is anticipated that technologies and applications related to gesture- and body-based interaction interfaces will become popular.
Conventionally, if it is intended to obtain an instruction of a markerless natural gesture or motion, an object feature in an image needs to be captured or matched by using an image processing technology in most cases. However, in a complex background environment, an image of an ordinary object or a natural gesture of a human body is easily interfered by variations of brightness, surrounding background or even other similar intrinsic features, which often results in unstable detection results. However, the human body, different from other hand-held remotes or specific apparatuses, does not have a fixed form, and in operation, gestures or body motions are generally subject to certain changes. Therefore, if only the color, template or movement track is used as a main feature for recognition, it is difficult to stably track the location of a target object (for example, a gesture). Therefore, in previous studies, the operating environment is usually limited under strict conditions (for example, pure background, light source with fixed brightness, and no other moving objects), thereby greatly limiting the application range. Meanwhile, as image processing generally involves a large amount of data operations, the response time is delayed, which cannot meet the requirement for real-time interaction.